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2023 International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2023

作者： Rambe, Khairul Hawani Ou, Chia-Ho International Master Program in Information Technology and Applications Sweden National Pingtung University Department of Computer Science and Information Engineering Taiwan

ISBN: (纸本)9798350324174

The Internet of Things (IoTs) have become ubiquitous in all aspects of public needs today. The application of IoT technology is crucial for promoting energy-saving behavior. This paper presents a control system used for smart home devices based on hand gesture control and Android applications. The hardware design uses the ESP32 microcontroller, which has an in-chip Wi-Fi module, making it very suitable for creating IoT application systems. The software was designed using the Arduino IDE, and the application display design was developed using Kodular Creator, which is used to control the lamps and switches. The experiment results show that the electrical equipment can be activated using the Android application with gesture sensors by waving down, up, left, and right. © 2023 IEEE.

关键词： Internet of things

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EESRGAN: Efficient & Effective Super-Resolution Generative Adversarial Network

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IETE Technical Review (Institution of Electronics and Telecommunication Engineers, India) 2024年第2期41卷 200-211页

作者： Tsai, An-Chao Tsou, Cheng-Han Wang, Jhing-Fa International Master Program of Information Technology and Application National Pingtung University Pingtung900 Taiwan Department of Electrical Engineering National Cheng Kung University Tainan Taiwan

In Taiwan, traditional production equipment for the mainframe panels is imported from overseas, and the parameters are adjusted through the operation panel for automated manufacturing. However, these parameters are slightly different from those used in Taiwan, requiring manual recording of warning parameters to ensure quality control. Currently, the only way to capture the operation records of these machines is by manually recording the system panel information, which is a time-consuming and laborious process that is expensive for production line personnel. In this work, we use image recognition to capture and analyze data externally without damaging the machine. This research improves the ESRGAN network to restore the image details and textures of the mainframe panels. It also captures relevant data with Google OCR to convert panel images into parameter values. The captured results are combined with data analysis to provide more accurate standard mainframe panel information. Even under different interference source conditions, data extraction and analysis can still be carried out to output the text files, effectively assisting the production line in recording the machine panel parameters and reducing personnel’s workload. © 2024 IETE.

关键词： Extraction

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A ShuffleNet Architecture-Based Multi-Layer Feature Scaling and Fusion Approach for Underwater Net Cage Damage Detection in Aquaculture

A ShuffleNet Architecture-Based Multi-Layer Feature Scaling ...

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2024 IEEE International Conference on Consumer Electronics-Asia, ICCE-Asia 2024

作者： Huang, Xiang-Rui Chen, Yi-Cheng Chen, Liang-Bi Hu, Wu-Chih National Penghu University of Science and Technology Master Program in Electrical Engineering and Computer Science Department of Electrical Engineering Penghu Taiwan National Penghu University of Science and Technology Department of Computer Science and Information Engineering Penghu Taiwan

ISBN: (纸本)9798331530839

In offshore aquaculture operations, personnel equipped with diving gear are often necessary to inspect the underwater net cages for damage, particularly on the sea floor. This manual inspection process is time-consuming and complex. To overcome this problem, this paper proposes a computer vision solution for identifying damage in underwater net cages to address the inefficiencies and challenges of traditional manual inspections. The proposed scheme utilizes a high-performance multi-branch computational architecture designed based on ShuffleNet architecture to detect net cage damage more efficiently. Experimental results demonstrate that this work performs well on the ImageNet ILSVRC-2010 dataset and achieves an accuracy of 88.54% in underwater net damage detection. © 2024 IEEE.

关键词： Aquaculture

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PreScienceMED: Leveraging Text Classification for Precise Disease Prediction 8

PreScienceMED: Leveraging Text Classification for Precise Di...

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8th IEEE International Conference on Distributed Computing, VLSI, Electrical Circuits and Robotics, DISCOVER 2024

作者： Prathwini Prathyakshini Nitte Department of Master of Computer Applications Karkala India Nitte Department of Information Science and Engineering Karkala India

ISBN: (数字)9798350350593

ISBN: (纸本)9798350350593

Emergent of new and modern technologies provide personalized solutions to health issues faced by the individuals. A chatbot using Natural language processing (NLP) is proposed which can detect relevant disease based on the user input. Different classification techniques such as Support vector Machine (SVM), Random Forest, Gaussian Naive Bayes and Decision Tree are used in detecting the relevant diseases with each disease containing 17 symptoms. Based on the symptoms the all the models can detect the diseases out of which Random Forest yields better accuracy score of 99.59%. Hence the proposed model can detect the diseases based on user queries. The study utilizes machine learning algorithms in order to automatically classify medical data based on the symptoms, reducing the reliance on manual analysis, and increasing efficiency. © 2024 IEEE.

关键词： Random forests

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Style Transfer of Musical Performance Expression Using Note Classification Based on the Implication-Realization Model 23

Style Transfer of Musical Performance Expression Using Note ...

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7th International Conference on computer Science and Application engineering, CSAE 2023

作者： Mizutani, Tetsuya Sasaki, Shigefumi Department of Information Engineering University of Tsukuba Tsukuba Japan Master's Program in Computer Science University of Tsukuba Tsukuba Japan

ISBN: (纸本)9798400700590

In recent years, the style transfer is being studied in the field of AI. It extracts a style from one data set and applies to another data set. This technique is actively studied mainly in computer vision. It is also being studied in music and speech processing with many deep learning methods. However, no research focused on changes in performance expression of music. Performance expression of music refers to the player's artistic interpretation of a piece of music, the changes in performance, and the techniques used to achieve these changes. Changes in performance are represented by slow and fast beats, changes in strength and weakness. In this study, as a part of the study of analysis and creation of performance expression models of music, the image style transfer method is applied to musical expression. In addition, in order to analyze the relationship between musical structure and musical expression, the implication-realization model of music theory is used to extract the structure of music to improve the performance of style transfer. The analysis result shows that the I-R model captures the feature of musical expression well, and moreover, the style transfer method is shown to be useful for analyzing performance expression of music. It will lead to the study of music performance expression style extraction and will contribute to the analysis and creation of performance expression models of music. © 2023 ACM.

关键词： Music

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The Efficient Traffic Sign Detection and Recognition for Taiwan Road Using YOLO Model with Hybrid Dataset 9

The Efficient Traffic Sign Detection and Recognition for Tai...

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9th International Conference on Applied System Innovation, ICASI 2023

作者： Suwattanapunkul, Taweelap Wang, Lung-Jen National Pingtung University International Master Program in Information Technology and Applications Taiwan National Pingtung University Department of Computer Science and Information Engineering Taiwan

ISBN: (纸本)9798350398380

According to the trend of worldwide car sales have grown up, this cause may increase accidents on the road due to human error. The self-driverless car has been developed to solve this problem. One task of the self-driverless car is traffic sign detection and recognition (TSDR), which will help drivers notify the traffic sign installed on the road in advance. Taiwan roads have specific traffic signs, and no Taiwan traffic sign public dataset is available. In this paper, our proposed object detection method was experimentally performed using YOLOv5s6 and YOLOv8s models on three different datasets, as Tsinghua-Tencent 100K (TT100k), the self-created Taiwan traffic sign (TWTS), and the hybrid dataset, which combine the traffic scenes between TT100k and TWTS dataset. The output results from each dataset and each model, which is trained on the same parameter, will be compared to validate the proposed method. The experiment results' comparison of the hybrid dataset between YOLOv5s6 and YOLOv8s models display the results of the mAP@.5 is about 65% and 76.2%, respectively, which means the performance of the YOLOv8s is higher than the YOLOv5s6 when using hybrid dataset. © 2023 IEEE.

关键词： Object detection

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ESG Investing: A Statistically Valid Approach to Data-Driven Decision Making and the Impact of ESG Factors on Stock Returns and Risk

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IEEE Access 2024年 12卷 69434-69444页

作者： Teja, Kamurthi Ravi Liu, Chuan-Ming National Taipei University of Technology International Program of Electrical Engineering and Computer Science Taipei10608 Taiwan National Taipei University of Technology Department of Computer Science and Information Engineering Taipei10608 Taiwan

This study examines the impact of environmental, social, and governance (ESG) factors on economic investment from a statistical perspective, aiming to develop a tested investment strategy that capitalizes on the connection between ESG factors and financial performance. ESG investing: A statistically valid approach to data-driven decision-making (ESGI-SVADDM) investment strategy is based on a rigorous, statistically valid approach that utilizes data, math, statistics, and data science libraries to drive investment decisions, eliminating the need for personal opinions and subjectivity. The process includes establishing an investment thesis, formulating testable hypotheses (HPS), retrieving and refining relevant data, calculating relevant measures, and testing and validating all hypotheses. The study uses S&P 500 stock data and ESG data from Sustainalytics to test the hypotheses. The empirical tests conducted revealed a negative correlation between ESG risk and expected returns, as well as a positive trend in the relationship between ESG risk and the overall risk of stocks. Moreover, the study found that higher ESG risk scores are associated with lower returns for investors, and that adopting a strategy of investing in stocks with low ESG risk and shorting stocks with high ESG risk yields superior returns compared to the market portfolio. © 2013 IEEE.

关键词： Investments

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Random Number Generator for Securing Data Exchange in Smart Factory: Recent Trends and Best Practices 3

Random Number Generator for Securing Data Exchange in Smart ...

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3rd International Conference on computer Technologies, ICCTech 2024

作者： Sama, Andi Meyliana Heryadi, Yaya Sahroni, Taufik Roni Bina Nusantara University Binus Graduate Program - Computer Science Computer Science Department Jakarta11480 Indonesia Bina Nusantara University School of Information System Information System Department Jakarta11480 Indonesia BINUS Graduate Program-Doctor of Computer Science Jakarta Computer Science Department Jakarta11530 Indonesia Bina Nusantara University BINUS Graduate Program - Master of Industrial Engineering Industrial Engineering Department Jakarta11480 Indonesia

ISBN: (纸本)9798350395419

IT/OT convergence in the form of a Cyber-Physical System (CPS) presents an opportunity to apply recent information Technology (IT) advancements to Operational Technology (OT). The IT/OT convergence introduces cyber security threats for OT. The OT communication protocols, for example, have limited or no security capabilities for securing data exchange beyond basic authentication. The RNG (Random Number Generator) function is crucial in PLC for producing the encryption keys or the initial seed for security algorithms. The software-based PRNG (Pseudo RNG) is the most common approach for RNG in OT, instead of hardware-based RNG. This study provides a systematic literature review of the most recent evidence in digital transformation to secure data exchange in smart factories, within OT, or across OT and IT settings. It does this by looking at the PRNG on PLC and identifying the most recent trends and best practices. The findings include up-to-date data on author countries' distribution, published journals, research trends, industries, and industry types. The findings also address whether data flow is encrypted or shared in plaintext to ensure secure data transfer between IT and legacy OT environments. This paper concludes that while there is known RNG implementation in the actual embedded system in ICS, there is no evidence in the literature for using RNG in ICS networks for PLC implementation to secure data transfer with encryption. © 2024 IEEE.

关键词： Data transfer

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Effective Bandwidth based Distributed DoS Attack Detection and Source Identification using Maximum Flow Techniques 3

Effective Bandwidth based Distributed DoS Attack Detection a...

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3rd International Conference on Intelligent Data Communication Technologies and Internet of Things, IDCIoT 2025

作者： Subburaj, T. Suthendran, K. Darshan, P. Deeraj, C. Jai Shankar, M. Pushpalatha, G. Department of Master of Computer Applications Rajarajeswari College of Engineering Bangalore India Department of Information Technology Kalasalingam Academy of Research and Education TamilNadu India

ISBN: (纸本)9798331527549

The DDoS attack is one of the most threatening factors affecting the internet services. Now days, most of the common attacks are targeting the gaming industry, online shopping websites followed by the software and media sectors. Many of the service providers are available to detect and prevent the DDoS attacks. But their software’s are not updated enough to detect the recent time attacks. Cyber security challenges include rising ransomware attacks, AI-powered threats, supply chain risks, and frequent data breaches. In the current IoT trend, available DDoS defenses aren’t sufficient. This work is aimed to propose a novel BW- DDoS attack detection approach based on maximum data flow identification in networks. The proposed method is faster and taking less number of iterations to determine the maximum data flow and also trace out the source of the attacks with minimum time compared with existing approaches. © 2025 IEEE.

关键词： Attacks BW-DDoS Entropy Maximum flow Trace out

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Design of an Automatic Price Tag System for Web-Based Retail Business 9

Design of an Automatic Price Tag System for Web-Based Retail...

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9th International Conference on information Management and Technology, ICIMTech 2024

作者： Liawatimena, Suryadiputra Gunawan, Devina Bina Nusantara University Automotive & Robotics Program Computer Engineering Department BINUS ASO School of Engineering Computer Science Deparment BINUS Graduate Program Master of Computer Science Jakarta11480 Indonesia Bina Nusantara University Automotive & Robotics Program Computer Engineering Department BINUS ASO School of Engineering Jakarta11480 Indonesia

ISBN: (纸本)9798350390025

Modern retail businesses face a significant challenge with the inefficiency of manually changing price labels on shelves. This manual process not only consumes valuable time and resources but also increases the likelihood of errors, leading to potential inaccuracies in pricing and a less streamlined shopping experience for customers. The proposed solution is the implementation of an Electronic Shelf Label (ESL) system that automatically displays the prices of goods on retail business shelves. This system connects a website (front end and back end) to e-paper via a Wi-Fi network and microcontroller, allowing retail business owners to update prices more easily. Additionally, buyers can search for desired items through the website. The results are the time to send data from the website to the e-paper, namely, to know the performance of the e-paper used. The average time required from 10 attempts to send data from the website to the e-paper is 20.935 seconds. Since the data is connected to the server and will be updated automatically, using this system will be more efficient than manually changing the price label, although it takes time to transfer data from the website to the e-paper. © 2024 IEEE.

关键词： Sales

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